@jnu.ac.in
Associate Professor Scholl of Computational and Integrative Sciences
Jawaharlal nehru university
MSc and Phd Chemistry IIT Kanpur India
Molecular modeling
Drug Design
Chemoinformatics
Bioinformatics
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Mohammad Kashif, Mohd Waseem, and Naidu Subbarao
Elsevier BV
Hari Madhav, G. Srinivas Reddy, Zeba Rizvi, Ehtesham Jameel, Tarosh S. Patel, Abdur Rahman, Vikas Yadav, Sadaf Fatima, Fatima Heyat, Kavita Pal,et al.
Royal Society of Chemistry (RSC)
The present study unveils a thorough reevaluation of diphenylmethylpiperazine and pyrazine-derived molecular hybrids, introducing them as a new class of antimalarials.
Neha Girdhar, Vikas Yadav, Nilima Kumari, Naidu Subbarao, and Annangarachari Krishnamachari
Informa UK Limited
The current trend in biomedical research is on prioritizing infections based on multidrug resistance. Elizabethkingia meningoseptica, a nosocomial infection-causing organism emerging from Neonatal Intensive Care Units (NICUs), leads to neonatal meningitis and sepsis resulting in severe illness, and, in some cases, fatal. Finding a solution remains challenging due to limited prior work. Translational S12 ribosomal proteins play a crucial role in decoding the codon-anticodon helix, which is essential for the survival of E. meningoseptica. These proteins do not exhibit significant similarity with humans, making them potential drug targets. An in silico study aims to identify specific inhibitors for E. meningoseptica ribosomal proteins among known bioactive compounds targeting prokaryotic 30S ribosomal protein. A 3D model of the 7JIL_h protein from Flavobacterium johnsoniae, showing 90% sequence similarity with the target protein was generated using SWISS-MODEL software. The model was validated through Molprobity v4.4, VERIFY 3D, Errata, and ProSA analysis, confirming conserved residues of the target protein. Insilico screening of known bioactive compounds and their analogs identified potential ligands for the target protein. Molecular Docking and post-docking analysis assessed the stability of the protein-ligand complexes among the shortlisted compounds. The top two compounds with high Gold fitness scores and low predicted binding energy underwent MD simulation and further estimation of free binding energy using the MM_PBSA module. These computationally shortlisted compounds, namely chEMBL 1323619 and chEMBL 312490 may be considered for future in-vivo studies as potential inhibitors against the modeled 30S ribosomal protein S12 of E. meningoseptica.Communicated by Ramaswamy H. Sarma.
Geet Madhukar and Naidu Subbarao
Informa UK Limited
Among the major altered pathways in head and neck squamous cell carcinoma, AKT/mTORC1/S6K and NRF2/KEAP1 pathway are quite significant. The overexpression and overstimulation of proteins from both these pathways makes them the promising candidates in cancer therapeutics. Inhibiting mTOR has been in research from past several decades but the tumour heterogeneity, and upregulation of several compensatory feed-back mechanisms, encourages to explore other downstream targets for inhibiting the pathway. One such downstream effectors of mTOR is S6K2. It is reported to be overexpressed in cancers such as head and neck cancer, breast cancer and prostate cancer. In case of NRF2/KEAP1 pathway, nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2) is overexpressed in ∼90% of head and neck squamous cell carcinoma (HNSCC) cases. It associates with poor survival rate and therapeutic resistance in HNSCC treatment. NRF2 pathway is the primary antioxidant pathway in the cell which also serves pro-tumorigenic functions, such as repression of apoptosis, cell proliferation support and chemoresistance. The aim of this work was to explore S6K2 and NRF2 and identify novel and potential inhibitors against them for treating head and neck squamous cell carcinoma. Since the crystal structure of S6K2 was not available at the time of this study, we modelled its structure using homology modelling and performed high throughput screening, molecular dynamics simulations, free energy calculations and protein-ligand interaction studies to identify the inhibitors. We identified natural compounds Crocin and Gypenoside XVII against S6K2 and Chebulinic acid and Sennoside A against NRF2. This study provides a significant in-depth understanding of the two studied pathways and therefore can be used in the development of potential therapeutics against HNSCC.Communicated by Ramaswamy H. Sarma.
Mohd Waseem, Shubhashis Das, Debarati Mondal, Monika Jain, Jitendra K. Thakur, and Naidu Subbarao
Elsevier BV
Ram Nayan Verma, Rahul Deo, Rakesh Srivastava, Naidu Subbarao, and Gajendra Pratap Singh
Springer Science and Business Media LLC
AbstractThe fuzzy support vector machine (FSVM) assigns each sample a fuzzy membership value based on its relevance, making it less sensitive to noise or outliers in the data. Although FSVM has had some success in avoiding the negative effects of noise, it uses hinge loss, which maximizes the shortest distance between two classes and is ineffective in dealing with feature noise near the decision boundary. Furthermore, whereas FSVM concentrates on misclassification errors, it neglects to consider the critical within-class scatter minimization. We present a Fuzzy support vector machine with pinball loss (FPin-SVM), which is a fuzzy extension of a reformulation of a recently proposed support vector machine with pinball loss (Pin-SVM) with several significant improvements, to improve the performance of FSVM. First, because we used the squared L2- norm of errors variables instead of the L1 norm, our FPin-SVM is a strongly convex minimization problem; second, to speed up the training procedure, solutions of the proposed FPin-SVM, as an unconstrained minimization problem, are obtained using the functional iterative and Newton methods. Third, it is proposed to solve the minimization problem directly in primal. Unlike FSVM and Pin-SVM, our FPin-SVM does not require a toolbox for optimization. We dig deeper into the features of FPin-SVM, such as noise insensitivity and within-class scatter minimization. We conducted experiments on synthetic and real-world datasets with various sounds to validate the usefulness of the suggested approach. Compared to the SVM, FSVM, and Pin-SVM, the presented approaches demonstrate equivalent or superior generalization performance in less training time.
Mohd Sajid Ali, Mohd Waseem, Naidu Subbarao, Abdullah Nasser Alahamed, and Hamad A. Al-Lohedan
Elsevier BV
Ankita Singh, Jitendra Kumar, Jyoti Verma, Naidu Subbarao, Shivani Sapra, Ashok Kumar Prasad, Vijay Kumar, and Deepti Sharma
Wiley
AbstractA candidate molecule 1‐(3‐(1H‐imidazol‐1‐yl) propyl)‐3‐(2,4‐difluorophenyl) thiourea (coded as ‘IR‐415’) exhibiting excellent antiviral efficacy in cell culture model was identified after a high‐throughput screening of the Maybridge library.[7] Twenty derivatives of IR‐415 hereafter referred to as DSA‐00 were synthesized and evaluated for their antiviral activity against hepatitis B virus (HBV) in cell culture. The HBV‐expressing HepG2.2.15 cells or HBV‐permissive HepG2‐hNTCP‐C4 cells were treated with DSA‐00 or its new derivatives. A significant and improved inhibition in viral DNA replication and secretion of hepatitis B surface antigen were observed in the presence two derivatives, viz., 1‐(2,4‐Difluoro‐phenyl)‐3‐(4‐imidazol‐1‐yl‐butyl)‐thiourea and 1‐(3,5‐Difluoro‐phenyl)‐3‐(4‐imidazol‐1‐yl‐butyl)‐thiourea. Consistent with these antiviral properties, our molecular docking studies predicted a high affinity interaction of these derivatives with HBx protein. Importantly, DSA‐00 and its derivatives exhibited minimal toxicity at higher concentrations. Thus, these derivatives have the potential to be developed as new therapeutics for mono or combination therapy for the management of HBV infection.
Madhulata Kumari and Naidu Subbarao
Future Science Ltd
Aim: To develop a one-dimensional convolutional neural network-based quantitative structure–activity relationship (1D-CNN-QSAR) model to identify novel anthrax inhibitors and analyze chemical space. Methods: We developed a 1D-CNN-QSAR model to identify novel anthrax inhibitors. Results: The statistical results of the 1D-CNN-QSAR model showed a mean square error of 0.045 and a predicted correlation coefficient of 0.79 for the test set. Further, chemical space analysis showed more than 80% fragment pair similarity, with activity cliffs associated with carboxylic acid, 2-phenylfurans, N-phenyldihydropyrazole, N-phenylpyrrole, furan, 4-methylene-1H-pyrazol-5-one, phenylimidazole, phenylpyrrole and phenylpyrazolidine. Conclusion: These fragments may serve as the basis for developing potent novel drug candidates for anthrax. Finally, we concluded that our proposed 1D-CNN-QSAR model and fingerprint analysis might be used to discover potential anthrax drug candidates.
Maneesha Pathak, Anita Singh, Pooja Rawal, Arcahana N Sah, and Subbarao Naidu
BSP Books Private Limited
Background of the Topic: Drug discovery employs bioinformatics and computational biology (CADD) approaches for the identification and optimization of lead compounds. The PARP-1 is the member of the PARP family. PARP-1 is the enzyme that repairs the DNA damage in cancer cell hence it is selected as the target for the study. PARP inhibitors were shown the prominent results in the treatment of different kinds of malignancies due to loss of function of BRCA1/2 genes.
 Methodology: Based on literature review, database search, ADME and MD simulation, top 10 selected ligands were screened and tested against PARP-1 (4R6E) protein using molecular docking (Glide and Gold software), protein ligand interaction by LIGPLOT analysis. Molecular simulation studies were performed using DESMOND software afterwards on the top compound (CHEMBL378794).
 Results: All top 10 compounds showed binding affinity based inhibitory potential against the PARP-1 protein. The highest binding affinities from top 10 compounds towards anticancer targets were exhibited by CHEMBL378794 and CHEMBL245559. 
 Discussion: The comparative analysis of 4R6E and the identified hits using MD simulation exhibited better stability of the binding domain with these molecules suggesting their strong interaction and selectivity towards PARP-1. 
 Conclusion: This study showed the significant results in cancer treatment and their strong interaction with PARP-1 binding BRCT domain. Hence, these molecules could further be carried forward to explore their potency against PARP-1 sensitive cancer.
Prassan Choudhary, Mohd Waseem, Sunil Kumar, Naidu Subbarao, Shilpi Srivastava, and Hillol Chakdar
Springer Science and Business Media LLC
Jyoti Verma, Pragyan Parimita Rath, Samudrala Gourinath, and Naidu Subbarao
Informa UK Limited
The SARS-CoV-2, responsible for the COVID-19 pandemic has wrecked devastation throughout the globe. The SARS-CoV-2 spike (S) glycoprotein plays crucial role in virus attachment, fusion, and entry. This study aims to identify inhibitors targeting the receptor binding domain (RBD) of the S protein using computational and experimental techniques. We carried out virtual screening of four datasets against the S-RBD. Six potential candidate inhibitors were selected for experimental evaluation. Here, we provide experimental evidence that the molecules 9‴-MethyllithosperMate, Epimedin A, Pentagalloylglucose, and Theaflavin-3-gallate have a high binding affinity towards SARS-CoV-2 S-RBD. 9‴-MethyllithosperMate with a KD value of 1.3 nM serves as the best inhibitor, followed by others with KD values in micromolar range. We performed molecular dynamics simulation to assess the binding stability of these inhibitors. Hence, our study reports novel inhibitors against the SARS-CoV-2 S-RBD and their predicted binding mode also suggest the possibility to interfere with the ACE2 binding.Communicated by Ramaswamy H. Sarma.
Adity Raturi, Vikas Yadav, Nasimul Hoda, Naidu Subbarao, and Saif Ali Chaudhry
Informa UK Limited
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease's onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our in-silico study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer's and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer's drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer's treatment. Further in vitro and in vivo studies are warranted to explore these findings.Communicated by Ramaswamy H. Sarma.
Jigyasa Verma, Neha Kaushal, Manish Manish, Naidu Subbarao, Venera Shakirova, Ekaterina Martynova, Rongzeng Liu, Shaimaa Hamza, Albert A. Rizvanov, Svetlana F. Khaiboullina,et al.
Informa UK Limited
The emergence of the new SARS-CoV-2 variants has led to major concern regarding the efficacy of approved vaccines. Nucleocapsid is a conserved structural protein essential for replication of the virus. This study focuses on identifying conserved epitopes on the nucleocapsid (N) protein of SARS-CoV-2. Using 510 unique amino acid sequences of SARS-CoV-2 N protein, two peptides (193 and 215 aa) with 90% conservancy were selected for T cell epitope prediction. Three immunogenic peptides containing multiple T cell epitopes were identified which were devoid of autoimmune and allergic immune response. These peptides were also conserved (100%) in recent Omicron variants reported in Jan-August 2023. HLA analysis reveals that these peptides are predicted as binding to large number of HLA alleles and 71-90% population coverage in six continents. Identified peptides displayed good binding score with both HLA class I and HLA class II molecules in the docking study. Also, a vaccine construct docked with TLR-4 receptor displays strong interaction with 20 hydrogen bonds and molecular simulation analysis reveals that docked complex are stable. Additionally, the immunogenicity of these N protein peptides was confirmed using SARS-CoV-2 convalescent serum samples. We conclude that the identified N protein peptides contain highly conserved and antigenic epitopes which could be used as a target for the future vaccine development against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
Sumit Sheoran, Swati Arora, Tanmayee Basu, Swati Negi, Naidu Subbarao, Anupam Kumar, Himanshu Singh, Dhamodharan Prabhu, Atul Kumar Upadhyay, Neeraj Kumar,et al.
Informa UK Limited
Prostate cancer is the second most dangerous cancer type worldwide. While various treatment options are present i.e. agonists and antagonists, their utilization leads to adverse effects and due to this resistance developing, ultimately the outcome is remission. So, to overcome this issue, we have undertaken an in-silico investigation to identify promising and unique flavonoid candidates for combating prostate cancer. Using GOLD software, the study assessed the effectiveness of 560 natural secondary polyphenols against CDKN2. Protein Data Bank was used to retrieve the 3D crystal structure of CDKN2 (PDB Id: 4EK3) and we retrieved the structure of selected secondary polyphenols from the PubChem database. The compound Diosmetin shows the highest GOLD score with the selected Protein i.e. CDKN2 which is 58.72. To better understand the 2-dimensional and 3-dimensional interactions, the interacting amino acid residues were visualised using Discovery Studio 3.5 and Maestro 13.5. Using Schrodinger-Glide, the Diosmetin and CDKN2 were re-docked, and decoy ligands were docked to CDKN2, which was used to further ascertain the study. The ligands with the highest Gold score were forecasted for pharmacokinetics characteristics, and the results were tabulated and analysed. Utilising the Gromacs software and Desmond packages, 100 ns of Diosmetin molecular dynamics simulations were run to evaluate the structural persistence and variations of protein-ligand complexes. Additionally, our investigation revealed that Diosmetin had a better binding affinity with CDKN2 measuring 58.72, and it also showed remarkable stability across a 100-ns simulation. Thus, following in-vitro and in-vivo clinical studies, diosmetin might lead to the Prostate regimen.Communicated by Ramaswamy H. Sarma.
Sudatta Dey, Isha Nagpal, Priyanka Sow, Rishita Dey, Arnob Chakrovorty, Banani Bhattacharjee, Saikat Saha, Avishek Majumder, Manindranath Bera, Naidu Subbarao,et al.
Informa UK Limited
The present study tends to evaluate the possible potential of bio-active Morroniside (MOR), against alloxan (ALX)-induced genotoxicity and hyperglycaemia. In silico prediction revealed the interaction of MOR with Poly (ADP-ribose) polymerase (PARP) protein which corroborated well with experimental in vitro L6 cell line and in vivo mice models. Data revealed the efficacy of MOR in the selective activation of PARP protein and modulating other stress proteins NF-κB, and TNF-α to initiate protective potential against ALX-induced genotoxicity and hyperglycaemia. Further, the strong interaction of MOR with CT-DNA (calf thymus DNA) analyzed through CD spectroscopy, UV-Vis study and ITC data revealed the concerted action of bio-factors involved in inhibiting chromosomal aberration and micronucleus formation associated with DNA damage. Finally, MOR does not play any role in microbial growth inhibition which often occurs due to hyperglycemic dysbiosis. Thus, from the overall findings, we may conclude that MOR could be a potential drug candidate for the therapeutic management of induced-hyperglycaemia and genotoxicity.Communicated by Ramaswamy H. Sarma.
Manish Manish, Smriti Mishra, Monika Pahuja, Ayush Anand, Naidu Subbarao, and Ram Samudrala
Springer US
Mohammad Kashif and Naidu Subbarao
Informa UK Limited
Glutamine Synthetase (GS) is functionally important in many pathogens, so its viability as a drug target has been widely investigated. We identified Leishmania major glutamine synthetase (Lm-GS) as an appealing target for developing potential leishmaniasis inhibitors. Comparative modeling, virtual screening, MD simulations along with MM-PBSA analyses were performed and two FDA approved compounds namely Chlortalidone (id ZINC00020253) and Ciprofloxacin (id ZINC00020220) were identified as potential inhibitor among the screened library. These compounds may be used as a lead molecule, although additional in vitro and in vivo testing is required to establish its anti-leishmanial effect. Hence, the goal of this study was to locate and identify certain medications that were previously FDA-approved for definite disorders and that might show anti-leishmanial effect. Due to GS's presence in additional Leishmania species, a novel medication docked with Lm-GS may have broad anti-leishmania efficacy.Communicated by Ramaswamy H. Sarma.
Ananyaa Agrawal, Pratibha Chanana, Vikas Yadav, Vilakshan Bhutani, Naidu Subbarao, and Aradhana Srivastava
Informa UK Limited
The objective of the study was to identify potential inhibitors of Influenza surface Hemagglutinin (HA), which plays key role in the entry and replication of Influenza virus into the host cell. As ligands, seven vitamins and their derivatives were selected after initial screening based on their metabolizable capacity with no reported side effects, for in silico studies. Docking, and Post docking analysis (X Score and Ligplot+) were performed against nine Influenza HA targets for the vitamins and its derivatives. 'Vitamin Derivatives' with top docking score were further analysed by MD Simulations and free energy was calculated using MMGBSA module. FMNNa and FMNCa displayed high binding free energy with Influenza HA, thereby exhibiting potential as HA inhibitors. Communicated by Ramaswamy H. Sarma.
Govinda Rao Dabburu, Aakriti Jain, Naidu Subbarao, and Manish Kumar
Informa UK Limited
Malaria is one of the major diseases of concern worldwide, especially in the African regions. According to a recent WHO report, 95% of deaths that occur due to malaria are in the African regions. Resistance to present antimalarial drugs is increasing rapidly and becoming a problem of concern. M17 Leucyl Aminopeptidase (PfM17LAP) and vacuolar Plasmepsins (PfPM) are two important enzymes involved in the haemoglobin degradation pathway of Plasmodium falciparum. PfM17LAP regulates the release of amino acids and PfPM mediates the conversion of haemoglobin proteins to oligopeptides. These enzymes thus play an essential role in the survival of malaria parasites inside the human body. In the present study, we used in-silico molecular docking, simulation and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) studies to find potential dual inhibitors of PfPM and PfM17LAP using the ChEMBL antimalarial library. Absorption, distribution, metabolism, excretion and toxicity (ADMET) profiling of the top ten ranked molecules was done using the BIOVIA Discovery Studio. The present investigation revealed that the compound CHEMBL426945 is stable in the binding site of both PfPM and PfM17LAP. In this study, we have reported novel dual-inhibitors that may act better than the present antimalarial drugs.Communicated by Ramaswamy H. Sarma.
Mohd Waseem, Jitendra K. Thakur, and Naidu Subbarao
Informa UK Limited
Lanosterol 14-α demethylase (LDM) is one of the promising drug targets of azoles antifungal. In this study, we have screened a large number of small molecules from different chemical databases (ZINC, DrugBank, ChEMBL, and ChemDiv) to find out novel and potential inhibitors of LDM. As a result, from more than a hundred thousand molecules, the two best candidates, C1 (ZINC000299817826) and C3 (ZINC000095786149), were selected from the top-scoring compounds and further validated in Molecular Dynamic (MD) simulation. The Glide scores of C1 and C3 were -19.33 kcal/mol and -19.13 kcal/mol, suggesting that these compounds bind with LDM with higher binding affinity than the benchmark compound (itraconazole), which has a Glide score of -6.85 kcal/mol. Docking poses reveal that the compounds C1 and C3 bind to the outermost region of the LDM binding site, which can prevent the lanosterol from getting into the catalytic pocket. Furthermore, MD simulation studies were performed to assess the stability of C1 and C3 in complex with LDM and were found to be stable over the 100 nanosecond simulation time. Binding free energy calculated by the MMPBSA method suggested that the C3 forms a more stable complex with the LDM as close to the benchmark compounds. Among the top selected molecules, C1 and C3 were predicted to be the significant inhibitors of LDM.Communicated by Ramaswamy H. Sarma.
Jyoti Verma and Naidu Subbarao
Informa UK Limited
Chikungunya virus (CHIKV) is an arthritogenic arbovirus responsible for re-emerging epidemics of Chikungunya fever around the world for centuries. Chikungunya has become endemic in Africa, Southeast Asia, the Indian subcontinent, and subtropical regions of the Americas. The unavailability of antiviral therapy or vaccine against the CHIKV and its continuous re-emergence demands an urgent need to develop potential candidate therapeutics. CHIKV entry into the host cell is mediated by its envelope proteins engaging the cellular receptor MXRA8 to invade the susceptible cells. We report here two essential target binding sites at the CHIKV E1-E2 proteins by identifying hotspot regions at the E1-E2-MXRA8 binding interface. Further, we employed high throughput computational screening to identify potential small molecule protein-protein interaction (PPI) modulators which could effectively bind at the identified target sites. Molecular dynamics simulations and binding free energy calculations confirmed the stability of three compounds, viz., ZINC299817498, ZINC584908978, and LAS52155651, at both the predicted interface binding sites. The polar and charged residues at the interface were responsible for energetically holding the ligands at the binding sites. Altogether, our findings suggest that the predicted target binding sites at the E1-E2 dimer could be essential to block the receptor interaction as well as the fusion process of the CHIKV particles. Thus, we identified a few small molecule PPI inhibitors with great potential to block the E1-E2-MXRA8 interaction and act as promising templates to design anti-CHIKV drugs.Communicated by Ramaswamy H. Sarma.
Madhulata Kumari, Mohd Waseem, and Naidu Subbarao
Informa UK Limited
Abstract In the present study, we generated a ligand-based scaffold model from a known bioactive datasets of mur enzymes of other species to identify multi-targeting inhibitors as antitubercular agents. Compounds in the ChEMBL database were first filtered to screen for substructure molecules ofMtb’s multi-target enzymes. 5′-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine has been identified as scaffold to develop compounds targeting Mtb’s mur enzymes. A library of Murcko scaffolds was extracted and evaluated for their in-silico antitubercular activity against Mtb’s mur enzymes. The screened compounds were subjected to molecular docking, molecular dynamics simulations, MM/PBSA calculation with Mtb’s mur enzymes to evaluate the mechanism of interaction to assess inhibitory activity against the target protein. The results revealed that 15 compounds have higher docking scores and good interactions with multiple mur enzymes of Mtb. From the docking analysis, compound HPT had the best score and binding affinity with the all mur enzymes. Further, protein-ligand interactions were evaluated by molecular dynamics simulations to assess their stability throughout 100 ns period. From the MD trajectory, we calculated RMSD, RMSF, Rg, PCA, DCCM, FEL, hydrogen bonding, and vector motion. Furthermore, the binding free energies of the all nine mur enzymes with compound HPT exhibited good binding affinity might show the anti-mycobacterial activity. The compound HPT revealed from this computational study could act as potent anti-mycobacterial inhibitors and further serve as lead scaffolds to develop more potent pharmaceutical molecules targeting multiple mur enzymes of Mtb based on 5′-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine in the future. Communicated by Ramaswamy H. Sarma
Ram Nayan Verma, Md. Zubbair Malik, Gajendra Pratap Singh, and Naidu Subbarao
Elsevier BV
Manish Manish, Smriti Mishra, Ayush Anand, and Naidu Subbarao
Elsevier BV